DESCRIPTION : Key job responsibilities

- Lead and develop a team of data engineers and SDEs, hiring, mentoring, setting technical direction, managing performance and growth opportunities.
- Own the data platform strategy and roadmap for the team’s portfolio, including multiple Redshift clusters, ETL/ELT pipelines, and data models that serve analytics, data science, and business stakeholders.
- Manage and optimize Redshift, druid and low-latency retrieval infrastructure, ensuring performance, cost efficiency, availability, and scalability across multiple clusters serving diverse business lines.
- Establish and enforce data governance, quality, and reliability standards, implementing monitoring, alerting, SLAs, and data quality frameworks across the team’s data assets.
- Partner cross-functionally with product managers, data scientists, BI engineers, and software engineers to translate business requirements into scalable data architecture and pipeline solutions.
- Represent data engineering in planning and leadership forums, contributing to annual planning, QBRs, and roadmap reviews. Communicate trade-offs, capacity constraints, and investment needs clearly to senior leadership.
- Drive operational excellence, owning on-call processes, incident response, COE follow-ups, and continuous improvement of the team’s operational posture.

A day in the life

Sales Data Services team is part of Sales AI,



a central data and science organization within Sales Intelligence, Technology, & Enablement organization (SITE) that powers Ad Sales selling motions and workflows via a suite of AI/ML services. Sales AI’s mission is to equip Sales with the data

- and science-backed intelligence they need (and when they need it) to improve their selling motions from routine practices to peak performance.

BASIC QUALIFICATIONS :

- 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
- 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
- 5+ years of data engineering experience
- 2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
- Experience managing a technical team
- Experience communicating to senior management and customers verbally and in writing
- Experience leading and influencing the data or BI strategy of your team or organization
- Experience in at least one contemporary scripting or programming language, such as Python, Java, Scala, or NodeJS

PREFERRED QUALIFICATIONS :

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)

📌 Data Engineering Manager, Sales Data Services (Sds) (Bengaluru)
🏢 ADCI - Karnataka
📍 Bengaluru